Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation
(2015)
Presentation / Conference Contribution
Navarro, J., Wagner, C., & Aickelin, U. Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation. Presented at 2015 IEEE Symposium Series on Computational Intelligence
Fuzzy Rule-Based Classification Systems (FRBCSs) have the potential to provide so-called interpretable classifiers, i.e. classifiers which can be introspective, understood, validated and augmented by human experts by relying on fuzzy-set based rules.... Read More about Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation.